Senior Data Scientist

Location Name: Pune Corporate Office - Mantri

Job Purpose

To design, develop, and implement AI and machine learning models for search systems that power scalable and intelligent search experiences at BFL. The role is primarily technical, focusing on hands-on coding, prototyping, and deploying ML models to improve search accuracy, ranking, and personalization.

Duties And Responsibilities

•  Develop and implement algorithms to improve indexing, ranking, and query relevance.
•  Work on NLP-driven search features including query expansion, synonym handling, and semantic search.
•  Contribute to building taxonomy, metadata, and ontology models for search optimization.
•  Write clean, efficient, and scalable code for ML/AI pipelines.
•  Support deployment of ML models into production with CI/CD pipelines.
•  Perform data preprocessing, feature engineering, and model training for search-related problems.
•  Run experiments, analyze results, and recommend improvements.
•  Collaborate with product teams and engineers to integrate search models into applications.
•  Stay updated with the latest research in search, NLP, and machine learning.
  
  
  

•  Technical choices on coding approaches, algorithms, and frameworks for assigned tasks.
•  Recommendations on model tuning, evaluation metrics, and data preprocessing methods.
•  Bug fixes, performance improvements, and solution enhancements within assigned scope.
  
  
  

•  Ensuring accuracy, latency, and scalability of search models in production.
•  Balancing experimentation with delivery timelines.
•  Debugging and fine-tuning ML pipelines in real-time environments.
•  Applying academic/industry research in a business production context.
  
  
  

•  BE/BTech/MSc/MTech in Computer Science, Statistics, Mathematics, or related fields.
  
  
  

•  2–5 years of experience in AI/ML, NLP, or Search/Information Retrieval.
•  Hands-on experience with deploying or supporting ML-based systems.
  
  
  

•  Strong coding in Python (preferred), Java, or Scala.
•  Experience with ML/DL frameworks: TensorFlow, PyTorch, scikit-learn.
•  Knowledge of NLP techniques for search (tokenization, embeddings, semantic search).
•  Familiarity with SQL/NoSQL databases (MongoDB, Cassandra, etc.).
•  Basic exposure to CI/CD, Git, testing, and Linux.
  
  
  

•  Experience with Elasticsearch/Solr, Lucene-based engines.
•  Exposure to cloud platforms (Azure/AWS/GCP) for ML model deployment.
•  Knowledge of recommendation/personalization systems.
•  Contribution to open-source projects or academic research in AI/ML.